In silico prediction of conserved microRNAs and their targets from the Asian rice gall midge (Orseolia oryzae) expressed sequence tags

Abstract

Using computational tools, the expressed sequence tags (EST) database of the rice gall midge Orseolia oryzae, a major insect pest of rice, was analyzed to predict non-coding RNAs involved in regulation of different biological processes. Using a simple protocol pipeline 10 miRNA families along with other non-coding RNAs (snRNAs, rRNAs, snoRNAs and others) were predicted. ncRNAs are mainly associated with transcription, translation, splicing and nuclear export. The predicted targets of these 10 miRNAs could be further divided into 8 functional categories after Gene Ontology analysis. These miRNAs pertain to categories that are known to control a variety of biological processes mainly related to development, genes and neurotransmitters related to the CNS maintenance and signalling within the cell. This was further corroborated with stem loop RT-PCR analysis of their expression in maggots and pupae of the insect. Data presented demonstrate that EST database of organisms could be put to use to predict conserved miRNAs and their putative targets. Further, results from the current study indicate that such studies involving prediction and/or identification of miRNAs and other non-coding RNAs as regulators within the Asian rice gall midge genome would help better understand gall midge-rice interactions.